DSLT_10_29_24ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "collapsed_sections": [
        "Uyn-xo-J12Wb",
        "anqht7410gJB"
      ],
      "authorship_tag": "ABX9TyPYIIKjMhvtRobRbbSXlFIW",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/bindersarah/Fly-Brain-Image-Processing/blob/main/DSLT_10_29_24ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "5FTj22hKsgch"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import h5py\n",
        "import cv2\n",
        "import tempfile\n",
        "import imageio\n",
        "import pandas as pd\n",
        "get_ipython().run_line_magic('matplotlib', 'inline')\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.express as px\n",
        "\n",
        "import plotly.io as pio\n",
        "pio.renderers.default = 'browser'"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Transform h5j files to numpy arrays"
      ],
      "metadata": {
        "id": "Xuuajod-sqUl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def extract_channel(raw_data, nframes, height, width):\n",
        "    with tempfile.NamedTemporaryFile(delete=True, suffix='.mp4') as temp_file:\n",
        "        temp_file.write(raw_data)\n",
        "        temp_file_name = temp_file.name\n",
        "\n",
        "        # Create a reader object for the temporary file\n",
        "        reader = imageio.get_reader(temp_file_name, 'ffmpeg')\n",
        "        frames = np.empty((nframes, height, width), np.uint8)\n",
        "        for i in range(nframes):\n",
        "            frames[i] = reader.get_data(i)[:,:,0]\n",
        "    return frames\n",
        "\n",
        "def read_h5j(filename):\n",
        "    with h5py.File(filename, 'r') as h5file:\n",
        "        attributes = {}\n",
        "        for tmp in h5file.attrs:\n",
        "            attributes[tmp] = h5file.attrs[tmp]\n",
        "        channel_attributes = {}\n",
        "        for tmp in h5file['Channels'].attrs:\n",
        "            channel_attributes[tmp] = h5file['Channels'].attrs[tmp]\n",
        "        nframes = channel_attributes['frames'][0]\n",
        "        height = channel_attributes['height'][0] + channel_attributes['pad_bottom'][0]\n",
        "        width = channel_attributes['width'][0] + channel_attributes['pad_right'][0]\n",
        "        R = extract_channel(h5file[\"Channels\"]['Channel_0'][()].tobytes(), nframes, height, width)\n",
        "        G = extract_channel(h5file[\"Channels\"]['Channel_1'][()].tobytes(), nframes, height, width)\n",
        "        B = extract_channel(h5file[\"Channels\"]['Channel_2'][()].tobytes(), nframes, height, width)\n",
        "        RGB = np.concatenate((R[:,:,:,None], G[:,:,:,None], B[:,:,:,None]), axis = 3)              #create array of pixels per RBG\n",
        "        reference = extract_channel(h5file[\"Channels\"]['Channel_3'][()].tobytes(), nframes, height, width)\n",
        "    return RGB, reference, attributes\n"
      ],
      "metadata": {
        "id": "g0-upZJ_ssX4"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Sample Brain Image"
      ],
      "metadata": {
        "id": "gP0MTf0Ysx2G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# upload to colab if needed\n",
        "\n",
        "#RGB, reference, attributes = read_h5j('/R27C09-20181221_62_F1-f-40x-central-GAL4-JRC2018_FEMALE_40x-aligned_stack.h5j')\n",
        "\n",
        " #'R27C09-20181221_62_F1-f-40x-central-GAL4-JRC2018_FEMALE_40x-aligned_stack.h5j')"
      ],
      "metadata": {
        "id": "v5ZLliPns1Uz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Load test Image: 2D Image, 17 x 17 subsection"
      ],
      "metadata": {
        "id": "E3sJ11iEs53H"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "image = cv2.imread('dslt_test.jpg')\n",
        "\n",
        "# ensure in grayscale\n",
        "if len(image.shape) == 3:\n",
        "    image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n",
        "\n",
        "# resize\n",
        "image = cv2.resize(image, (203,270)) #203 x 270 pixels\n",
        "\n",
        "# select 17 x 17 pixel\n",
        "image1 = image[90-8:90+9, 100-8:100+9]\n",
        "\n",
        "# Display the loaded image\n",
        "plt.figure(figsize=(6, 6))\n",
        "plt.title(\"Loaded Grayscale Image\")\n",
        "plt.imshow(image1, cmap='gray')\n",
        "plt.axis('off')\n",
        "plt.show()\n",
        "\n",
        "# create coordinate grid 17 x 17\n",
        "X,Y = np.meshgrid(np.arange(-8,9), np.arange(-8,9))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 521
        },
        "id": "8egNYsljs5kr",
        "outputId": "e87dd8db-d37a-4df4-ef29-956110e226c7"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Rotate Image"
      ],
      "metadata": {
        "id": "iUauJsfVtNCg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Loop to rotate image1 8 different ways (first subsection)\n",
        "\n",
        "# define standard variables\n",
        "(X, Y) = image1.shape[:2]\n",
        "center = (Y // 2, X // 2)\n",
        "scale = 1.0\n",
        "angles_list = [22.5, 45.0, 67.5, 90.0, 112.5, 135.0, 157.5, 180.0]\n",
        "\n",
        "# Turn into Function\n",
        "def image_rotate(image):\n",
        "  for index, angle in enumerate(angles_list):\n",
        "    # define matrix\n",
        "    rotation_matrix = cv2.getRotationMatrix2D(center, angle, scale)\n",
        "\n",
        "    # rotate image\n",
        "    rotated_image = cv2.warpAffine(image, rotation_matrix, (Y, X))# rotate #**** change image1\n",
        "\n",
        "    # Display the rotated image\n",
        "    plt.figure(figsize=(6, 6))\n",
        "    plt.title(f\"Rotated Image at Index {index + 1}: {angle}°\")\n",
        "    plt.imshow(rotated_image, cmap='gray')\n",
        "    plt.axis('off')\n",
        "    plt.show()\n",
        "\n",
        "# run function on dslt test image\n",
        "image_rotate(image1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "SUrmNpVjtPBz",
        "outputId": "5726a96f-2185-4c74-9f96-9403b3b98b54"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Gaussian Weights"
      ],
      "metadata": {
        "id": "e6qSVJUgtWcg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Define the Gaussian weight function\n",
        "def gaussian_weights(size, sigma=2):\n",
        "    k = np.arange(-size // 2 + 1, size // 2 + 1)\n",
        "    weights = np.exp(-(k**2) / (2 *sigma*2)) ## coded wrong - as k*2\n",
        "\n",
        "# normalize to ensure values sum to 1\n",
        "# gaussian = gaussian / np.sum(gaussian)\n",
        "\n",
        "    # Plot the distribution\n",
        "    plt.figure(figsize=(10, 6))\n",
        "    plt.plot(k, weights / weights.sum(), 'b-o') # b-o = blue, solid line, circles\n",
        "    plt.title('Gaussian Distribution')\n",
        "    plt.xlabel('k')\n",
        "    plt.ylabel('Probability')\n",
        "    plt.grid(True)\n",
        "\n",
        "    return weights / weights.sum()  # Normalize so that the sum is 1\n",
        "    return plt.show()\n",
        "\n",
        "# Generate weights for a 17-pixel row\n",
        "gaussian_weights_1d = gaussian_weights(17)\n",
        "print(\"Gaussian weights: \", gaussian_weights_1d)\n",
        "\n",
        "# ensure weights sum to 1\n",
        "print(np.sum(gaussian_weights_1d)) # 1.0"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 668
        },
        "id": "_a6bsRVvxV_6",
        "outputId": "59d57055-3d5a-4806-e0dd-eb08e4b0fba4"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Gaussian weights:  [6.69162896e-05 4.36349021e-04 2.21596317e-03 8.76430436e-03\n",
            " 2.69959580e-02 6.47599366e-02 1.20987490e-01 1.76035759e-01\n",
            " 1.99474648e-01 1.76035759e-01 1.20987490e-01 6.47599366e-02\n",
            " 2.69959580e-02 8.76430436e-03 2.21596317e-03 4.36349021e-04\n",
            " 6.69162896e-05]\n",
            "1.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Calculate Threshold\n",
        "\n",
        "###1. Compute weighted pixels: center row pixels values * gaussian weights\n",
        "###2. Compute weighted sums per rotation\n",
        "###3. Compute Threshold by summing all 8 weighted sums"
      ],
      "metadata": {
        "id": "MEfa-ggUuP03"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Define the angles list (already provided earlier)\n",
        "angles_list = [22.5, 45.0, 67.5, 90.0, 112.5, 135.0, 157.5, 180.0]\n",
        "\n",
        "# Initialize a list to store weighted sums for each angle\n",
        "weighted_sums = []\n",
        "\n",
        "# Loop through all the rotation angles and calculate weighted sums\n",
        "for angle in angles_list:\n",
        "    # Perform the rotation\n",
        "    rotation_matrix = cv2.getRotationMatrix2D(center, angle, scale)\n",
        "    rotated_image1 = cv2.warpAffine(image1, rotation_matrix, (Y, X))\n",
        "\n",
        "    # Extract the pixel values along the x-axis (center row)\n",
        "    center_row_pixels = rotated_image1[8, :]  # Extract the 17 pixels from the rotated image\n",
        "\n",
        "    # Apply Gaussian weights\n",
        "    weighted_pixels = center_row_pixels * gaussian_weights_1d  # A * B\n",
        "\n",
        "    # Compute the weighted sum and store the result\n",
        "    weighted_sum = np.sum(weighted_pixels)\n",
        "    weighted_sums.append(weighted_sum)\n",
        "\n",
        "# Sum all the 8 weighted sums to compute the threshold\n",
        "threshold_value = np.sum(weighted_sums)\n",
        "\n",
        "# Output the threshold value\n",
        "print(\"Threshold value from 8 rotations:\", threshold_value)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-GI_PkQEuSKc",
        "outputId": "62dbf02c-5155-4c13-b36c-b3c646a9b0e1"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Threshold value from 8 rotations: 652.0638089752538\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Calc Min Threshold?"
      ],
      "metadata": {
        "id": "fezKU4nNuVah"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Constant value for the threshold comparison (set to 0 for now)\n",
        "constant = 0\n",
        "\n",
        "# Initialize an array to store all the threshold values for each rotation\n",
        "thresholds = []\n",
        "\n",
        "# Loop through all rotation angles and calculate the threshold for each rotation\n",
        "for angle in angles_list:\n",
        "    # Rotate the image\n",
        "    rotation_matrix = cv2.getRotationMatrix2D(center, angle, scale)\n",
        "    rotated_image1 = cv2.warpAffine(image1, rotation_matrix, (Y, X))\n",
        "\n",
        "    # Extract the center row of pixels (row 8, as it’s the center of the 17x17 window)\n",
        "    center_row_pixels = rotated_image1[8, :]  # 17-pixel row\n",
        "\n",
        "    # Apply Gaussian weights to the pixel values\n",
        "    weighted_pixels = center_row_pixels * gaussian_weights_1d  # A * B\n",
        "\n",
        "    # Calculate the weighted sum (threshold) for this angle\n",
        "    threshold = np.sum(weighted_pixels)\n",
        "    thresholds.append(threshold)\n",
        "\n",
        "# Find the minimum threshold across the 8 angles\n",
        "min_threshold = np.min(thresholds)\n",
        "\n",
        "# Now apply the decision rule for the center pixel of the original image1\n",
        "center_pixel_value = image1[8, 8]  # The center pixel of the original 17x17 window\n",
        "\n",
        "# Apply the decision rule: compare center pixel to min_threshold + constant\n",
        "if center_pixel_value > min_threshold + constant:\n",
        "    output_value = 1  # The pixel exceeds the threshold\n",
        "else:\n",
        "    output_value = 0  # The pixel does not exceed the threshold\n",
        "\n",
        "# Output the final decision\n",
        "print(\"Center pixel value:\", center_pixel_value)\n",
        "print(\"Minimum threshold across angles:\", min_threshold)\n",
        "print(\"Output value (1 for feature, 0 for no feature):\", output_value)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5CYrAOJguPim",
        "outputId": "1691ea33-38d9-41d2-d01c-d5d2022f24c7"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Center pixel value: 104\n",
            "Minimum threshold across angles: 73.29477623652053\n",
            "Output value (1 for feature, 0 for no feature): 1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Skip: accomplished via process_image\n",
        "## local_windows\n",
        "#### To identify all 17x17 patches"
      ],
      "metadata": {
        "id": "Uyn-xo-J12Wb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to identify patches\n",
        "def local_windows(image, patch_size=17):\n",
        "    # Get the dimensions of the image\n",
        "    img_height, img_width = image.shape\n",
        "\n",
        "    # Create an output image (same size as input) initialized with zeros\n",
        "    output_image = np.zeros_like(image)\n",
        "\n",
        "    # for output threshold\n",
        "    threshold = np.zeros_like(image)\n",
        "\n",
        "    # output angle\n",
        "    output_angle = np.zeros_like(image)\n",
        "\n",
        "    # Loop through every pixel, excluding the border (as we can't crop a 17x17 patch around the borders)\n",
        "    border = patch_size // 2\n",
        "    for i in range(border, img_height - border):\n",
        "        for j in range(border, img_width - border):\n",
        "            # Crop a 17x17 patch around the current pixel (i, j)\n",
        "            patch = image[i - border:i + border + 1, j - border:j + border + 1]\n",
        "\n",
        "            # Process the patch and get the output value (1 or 0)\n",
        "            output_threshold, angle = process_patch(patch, gaussian_weights_1d)\n",
        "            threshold[i,j] = output_threshold\n",
        "            output_angle[i,j] = angle\n",
        "\n",
        "            # compare to min_threshold\n",
        "            if image[i,j] > output_threshold + 2:\n",
        "                output_image[i,j] = 1  # Feature detected\n",
        "\n",
        "\n",
        "    return output_image, threshold, output_angle\n",
        "\n"
      ],
      "metadata": {
        "id": "OrWXpWWW173Z"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# process_patch\n",
        "#### To determine threshold for a single patch"
      ],
      "metadata": {
        "id": "tIYWv1apzAX0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Define rotation angles\n",
        "angles_list = [22.5, 45.0, 67.5, 90.0, 112.5, 135.0, 157.5, 180.0]\n",
        "\n",
        "# Function to process a single 17x17 patch and evaluate the center pixel\n",
        "def process_patch(patch, gaussian_weights_1d, constant=0):\n",
        "    (X, Y) = patch.shape[:2]\n",
        "    center = (Y // 2, X // 2)\n",
        "    scale = 1.0\n",
        "    weighted_sums = []\n",
        "\n",
        "    # Rotate patch and calculate weighted sum for each angle\n",
        "    for angle in angles_list:\n",
        "        rotation_matrix = cv2.getRotationMatrix2D(center, angle, scale)\n",
        "        rotated_patch = cv2.warpAffine(patch, rotation_matrix, (Y, X))\n",
        "\n",
        "        # Extract center row and apply Gaussian weights\n",
        "        center_row_pixels = rotated_patch[8, :]\n",
        "        weighted_pixels = center_row_pixels * gaussian_weights_1d\n",
        "        weighted_sums.append(np.sum(weighted_pixels))\n",
        "\n",
        "    # Determine minimum threshold from all rotations\n",
        "    min_threshold = np.min(weighted_sums)\n",
        "\n",
        "    # Evaluate if the center pixel exceeds the threshold\n",
        "    center_pixel_value = patch[8, 8]\n",
        "    return 1 if center_pixel_value > min_threshold else 0\n"
      ],
      "metadata": {
        "id": "cR5E46y8z2AU"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# process_image"
      ],
      "metadata": {
        "id": "hgJMSkUKz_sx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### define function"
      ],
      "metadata": {
        "id": "Mid5yKw-0NYx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to process the entire image\n",
        "def process_image(image, patch_size=17):\n",
        "    img_height, img_width = image.shape\n",
        "    output_image = np.zeros_like(image)\n",
        "    border = patch_size // 2\n",
        "\n",
        "    # Loop through each pixel, skipping borders # identifies all patches\n",
        "    for i in range(border, img_height - border):\n",
        "        for j in range(border, img_width - border):\n",
        "            # Extract 17x17 patch\n",
        "            patch = image[i - border:i + border + 1, j - border:j + border + 1]\n",
        "\n",
        "            # Process the patch and get result for the center pixel\n",
        "            output_image[i, j] = process_patch(patch, gaussian_weights_1d)\n",
        "\n",
        "    return output_image"
      ],
      "metadata": {
        "id": "hGSSxYuk0CH3"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Apply to DSLT image"
      ],
      "metadata": {
        "id": "KOz_WKKj0RAa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Load and preprocess the image (ensure it’s grayscale)\n",
        "image = cv2.imread('dslt_test.jpg', cv2.IMREAD_GRAYSCALE)\n",
        "\n",
        "# Check if the image was loaded correctly\n",
        "if image is None:\n",
        "    print(\"Error: Could not load the image. Please check the file path.\")\n",
        "else:\n",
        "    # Resize for testing purposes if needed\n",
        "    image = cv2.resize(image, (203, 270))\n",
        "\n",
        "    # Apply the image processing function\n",
        "    output_image = process_image(image)\n",
        "\n",
        "    # Display the processed image\n",
        "    plt.figure(figsize=(6, 6))\n",
        "    plt.title(\"Denoised Image with Local Threshold\")\n",
        "    plt.imshow(output_image, cmap='gray')\n",
        "    plt.axis('off')\n",
        "    plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 521
        },
        "id": "bcI7BRex0TvT",
        "outputId": "707cc70d-1c2a-41cc-8fae-f6499924be48"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Define Local Windows Function"
      ],
      "metadata": {
        "id": "anqht7410gJB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Function to identify patches\n",
        "def local_windows(image, patch_size=17):\n",
        "    # Get the dimensions of the image\n",
        "    img_height, img_width = image.shape\n",
        "\n",
        "    # Create an output image (same size as input) initialized with zeros\n",
        "    output_image = np.zeros_like(image)\n",
        "\n",
        "    # for output threshold\n",
        "    threshold = np.zeros_like(image)\n",
        "\n",
        "    # output angle\n",
        "    output_angle = np.zeros_like(image)\n",
        "\n",
        "    # Loop through every pixel, excluding the border (as we can't crop a 17x17 patch around the borders)\n",
        "    border = patch_size // 2\n",
        "    for i in range(border, img_height - border):\n",
        "        for j in range(border, img_width - border):\n",
        "            # Crop a 17x17 patch around the current pixel (i, j)\n",
        "            patch = image[i - border:i + border + 1, j - border:j + border + 1]\n",
        "\n",
        "            # Process the patch and get the output value (1 or 0)\n",
        "            output_threshold, angle = process_patch(patch, gaussian_weights_1d)\n",
        "            threshold[i,j] = output_threshold\n",
        "            output_angle[i,j] = angle\n",
        "\n",
        "            # compare to min_threshold\n",
        "            if image[i,j] > output_threshold + 2:\n",
        "                output_image[i,j] = 1  # Feature detected\n",
        "\n",
        "\n",
        "    return output_image, threshold, output_angle\n",
        "\n"
      ],
      "metadata": {
        "id": "k0hp5sru04oh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Apply to Kawase Image"
      ],
      "metadata": {
        "id": "P19oyZl20bOo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Load and preprocess the image (ensure it’s grayscale)\n",
        "image = cv2.imread('kawase_image.png', cv2.IMREAD_GRAYSCALE)\n",
        "\n",
        "# resize\n",
        "image = cv2.resize(image, (146, 123))\n",
        "\n",
        "#show\n",
        "plt.imshow(image, cmap = 'gray')\n",
        "\n",
        "# Check if the image was loaded correctly\n",
        "if image is None:\n",
        "    print(\"Error: Could not load the image. Please check the file path.\")\n",
        "else:\n",
        "    # Resize for testing purposes if needed\n",
        "    image = cv2.resize(image, (203, 270))\n",
        "\n",
        "    # Apply the image processing function\n",
        "    output_image = process_image(image) # process_image calls process_patch\n",
        "\n",
        "    # Display the processed image\n",
        "    plt.figure(figsize=(6, 6))\n",
        "    plt.title(\"Image with Local Threshold\")\n",
        "    plt.imshow(output_image, cmap='gray')\n",
        "    plt.axis('off')\n",
        "    plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 938
        },
        "id": "qU7lR0wH0gWe",
        "outputId": "78bed9ac-91a4-42b4-999b-7756ff2b3bfd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Process\n",
        "\n",
        "### 1. identify patches of 17x17 local windows\n",
        "### 2. Calculate threshold per patch\n",
        "### 3. Evaluate center pixel > min_threshold per local window"
      ],
      "metadata": {
        "id": "z4oqZ-uB1X-T"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Next Steps:\n",
        "10/25\n",
        "1. Try other patches (with more signal) and evaluate weighted sums\n",
        "2. Try equal weights 1/17 ...\n",
        "3. Try Hough Transform: what is ouput, and what feature can we use to determine if there is a line through the center\n",
        "10/29\n",
        "See Notebook Yiyin Shared in Slack:\n",
        "1. Try plotting yellow lines like in Kawase image (see paper) check we have the same orientation as yellow lines\n",
        "2. Play around with constant value ?\n",
        "\n"
      ],
      "metadata": {
        "id": "szb_Ltqv1lCL"
      }
    }
  ]
}